Radiopaque Wire Calibration for Biplanar X-Ray Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing radiographic imaging systems face challenges in generating real-time three-dimensional CT quality images for surgical navigation, particularly in reconstructing 3D volumes from biplanar radiographic images, due to inaccuracies in calibration and interference from traditional spherical markers, which complicate digital subtraction and introduce artifacts.
Innovation Solution
A wire-based calibration target is used, comprising thin wires at specific depths, with deep learning models to detect and label wires, allowing precise polynomial fitting and correction of image distortions, facilitating accurate 3D volume reconstruction and alignment of surgical instruments within the patient anatomy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional spherical markers are used for calibration, then calibration targets are visible in radiographic images, but they complicate digital subtraction and introduce artifacts
Solution Approach 1:
The patent changes the physical parameter of the calibration markers from spherical shapes to thin wire configurations. This parameter change maintains the markers' visibility in radiographic images while significantly reducing their cross-sectional area, which minimizes interference with digital subtraction processes and reduces artifact generation during image reconstruction.
Solution Approach 2:
The patent extracts the essential calibration function from traditional bulky spherical markers and implements it through thin wire structures. By removing the excessive material volume while preserving the radiopaque properties and geometric definition, the wire-based markers achieve calibration accuracy without the harmful side effects of large marker interference.
2Object-generated harmful factors
If wire-based calibration targets are used, then interference and artifacts are reduced, but detection and labeling of wires requires advanced deep learning models
Solution Approach 1:
The patent replaces traditional mechanical or manual wire detection and labeling methods with deep learning-based computer vision systems. This substitution enables automated detection and characterization of wire markers in radiographic images, handling the complexity of thin wire identification while maintaining processing efficiency and accuracy.
3Measurement precision
If polynomial fitting is used for wire detection, then image distortion correction is improved, but computational complexity increases
Solution Approach 1:
The patent applies polynomial fitting to wire centerlines as a preliminary processing step before final image reconstruction and distortion correction. By pre-characterizing the wire geometries and their deviations from ideal straight lines, the system establishes accurate reference models that guide subsequent correction algorithms, improving overall precision while managing computational load through staged processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables efficient, accurate, and cost-effective generation of real-time 3D CT quality images for surgical navigation, overcoming traditional calibration limitations by improving manufacturing, reducing interference, and enhancing robustness to occlusions.
Implementation Method 1
a calibration target comprising thin wires arranged at different depths within the body of the calibration target itself
Data Source
AI summary
A calibration target for use with a radiographic image detector includes a target body securable to the image detector and a plurality of radiopaque linear markers, e.g. wires, fixed to the target body, wherein access to the image detector by incident radiation is at least partially blocked by the plurality of linear markers. By using the geometric properties of wires and advanced detection techniques, a precise calibration suitable for high-quality, volumetric three-dimensional CT reconstruction from biplanar X-ray images is achieved.